docs(bench): qualitative real-recording pass — P1 cleanest + best punctuation, W4 worst
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@@ -69,6 +69,27 @@ Note the trade visible even here: Whisper punctuates richly; Parakeet's int8 out
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casing but **sparse punctuation** — a real consideration for notes.md readability (see
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integration costs).
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## Qualitative pass — real recording (2026-07-16 follow-up)
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`bench-corpus/test_wavs/bank_deposits.wav` (62 s real recording, 48 kHz stereo — financial
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disclosure read aloud; downmixed/resampled by the production reader). No reference transcript,
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so transcripts were compared by eye; raw hypotheses in `bench-results/raw-qual-bank-deposits.csv`
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(its WER column is against a placeholder — ignore it).
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- **P1 (parakeet t4):** cleanest of the three — zero audible-word errors, and the **best
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punctuation**, including commas around a parenthetical clause ("…the bank deposit details
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section, which appears later in this statement, for information…"). The "sparse punctuation"
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concern from the LibriSpeech sample did **not** reproduce on this longer real clip.
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- **W2 (Vulkan base.en):** near-perfect; one function-word slip ("effective for cash balances
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*and* your FDIC insured…" — W4 and P1 both hear "*in* your").
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- **W4 (NPU ONNX, shipping default):** worst of the three — "details" → "**D-Tales**" twice,
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"are SIPC protected" → "**or** SIPC protected", and a segmentation break at the end
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("statement period" → "**state. period.**").
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One clip, one speaker, clean audio — directionally consistent with the corpus WERs
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(P1 ≥ W2 > W4), and it removes punctuation as an argument against Parakeet. Multi-speaker
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crosstalk remains untested.
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## Pre-registered criteria, evaluated
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| Criterion | Result |
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@@ -104,17 +125,17 @@ contender remain in the harness as the documented attempt.
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**Integration costs before any default flip** (not solved by this bench): timestamped segments
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(sherpa-rs's `transducer` API returns text only; the C API exposes timestamps — small upstream
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PR or direct `-sys` call), punctuation restoration (sparse in Parakeet output; matters for
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notes.md), English-only v2 (v3 is multilingual — the whisper multilingual path must remain for
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PR or direct `-sys` call), punctuation restoration (sparse on short LibriSpeech clips, though
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the real-recording qualitative pass showed *good* punctuation on longer audio — may be a
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non-issue), English-only v2 (v3 is multilingual — the whisper multilingual path must remain for
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non-English), a ~660 MB model download, and the model catalog/dispatch work (same shape as the
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0.7.3 merged-decoder swap).
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## Caveats
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- LibriSpeech is clean read speech; WERs are comparative, not absolute product claims. The
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planned qualitative pass over real meeting audio was skipped because all retained recordings
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are vault-sealed (by design); to run it, export a meeting bundle from an unlocked session and
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drop the WAV into `bench-corpus/test_wavs/`.
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qualitative pass over a real recording was run as a follow-up (section above) — still
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single-speaker; multi-speaker meeting audio with crosstalk remains untested.
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- int8 quantization slightly penalizes Parakeet vs published fp32 figures — it *still* won by
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85 %; the fp32 bundle exists if a tighter number is ever needed.
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- Single machine, single run per cell (30 files each). Differences here are far larger than
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